Create README.md
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README.md
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https://archive.ics.uci.edu/dataset/331/sentiment+labelled+sentences
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This dataset was created for the Paper 'From Group to Individual Labels using Deep Features', Kotzias et. al,. KDD 2015
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Please cite the paper if you want to use it :)
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It contains sentences labelled with positive or negative sentiment, extracted from reviews of products, movies, and restaurants
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=======
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Format:
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=======
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sentence \t score \n
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=======
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Details:
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=======
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Score is either 1 (for positive) or 0 (for negative)
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The sentences come from three different websites/fields:
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imdb.com
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amazon.com
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yelp.com
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For each website, there exist 500 positive and 500 negative sentences. Those were selected randomly for larger datasets of reviews.
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We attempted to select sentences that have a clearly positive or negative connotaton, the goal was for no neutral sentences to be selected.
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For the full datasets look:
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imdb: Maas et. al., 2011 'Learning word vectors for sentiment analysis'
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amazon: McAuley et. al., 2013 'Hidden factors and hidden topics: Understanding rating dimensions with review text'
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yelp: Yelp dataset challenge http://www.yelp.com/dataset_challenge
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